摘要
智慧图书馆子系统是高校智慧校园系统的核心部件,它融合了云计算技术、边缘计算技术、物联网技术、人工智能技术。借助边缘计算技术,可以通过把计算资源和存储资源下沉到网络边缘的边缘服务器上。智能终端设备把任务卸载到边缘服务器上来处理,可以降低智能终端设备的任务处理时延和能源消耗,从而满足读者的随时随地的阅读需求。针对高校智慧图书馆边缘计算场景下的任务卸载决策问题,建立了系统模型、时延模型、能耗模型和多目标优化模型,给出了一种基于MOEA/D算法的卸载方案,并与本地执行的方案、随机卸载方案、基于遗传算法的卸载方案进行了对比实验。实验结果表明:给出的任务卸载方案能够有效降低智能终端设备的任务卸载时延和能耗,能满足智慧图书馆的任务卸载需求。
The smart library subsystem is the core component of the smart campus system,which integrates cloud computing technology,edge computing technology,Internet of things technology and artificial intelligence technology.With the help of edge computing technology,computing resources and storage resources can be sunk to the edge server at the edge of the network.The intelligent terminal device offloads the task to the edge server for processing,which can reduce the task processing delay and energy consumption of the intelligent terminal device,so as to meet the reader's reading needs anytime and anywhere.In this paper,aiming at the task offloading decision-making problem in the edge computing scenario of the University intelligent library,a system model,a time delay model,a energy consumption model and a multi-objective optimization model were established,and a offloading decision-making scheme based on MOEA/D algorithm was proposed,and the comparative experiments with the locally executed scheme,the random offloading scheme and the offloading scheme based on genetic algorithm were done.The experimental results show that the task offloading scheme presented in this paper can effectively reduce the task offloading delay and energy consumption of the intelligent terminal equipment,and can meet the task offloading requirements of the intelligent library.
作者
张青华
柴争义
ZHANG Qinghua;CHAI Zhengyi(Library of Tianjin Chengjian University,Tianjin 300384,China;School of Computer Science&Technology,Tiangong University,Tianjin 300387 China)
出处
《周口师范学院学报》
CAS
2023年第2期51-56,共6页
Journal of Zhoukou Normal University
基金
天津市自然科学基金项目“智慧车联网场景中云边协同计算及隐私数据保护的关键技术研究”(22JCZDJC00600)。
